方法对比
并排查看您选择的方法；存在差异的行会高亮显示。
| Cox比例风险模型× | 队列研究× | |
|---|---|---|
| 领域 | 流行病学 | 流行病学 |
| 方法族 | Process / pipeline | Process / pipeline |
| 起源年份≠ | 1972 | Mid-20th century (formal epidemiological design codified ~1950s) |
| 提出者≠ | Sir David Roxbee Cox | Doll & Hill (British Doctors Study, 1951); Snow (cholera, 1854) |
| 类型≠ | Semi-parametric regression model | Observational longitudinal study design |
| 开创性文献≠ | Cox, D. R. (1972). Regression models and life-tables. Journal of the Royal Statistical Society: Series B (Methodological), 34(2), 187–202. DOI ↗ | Rothman, K. J., Greenland, S., & Lash, T. L. (2008). Modern Epidemiology (3rd ed.). Lippincott Williams & Wilkins. ISBN: 978-0781755641 |
| 别名 | Cox regression, Cox PH model, proportional hazards model, CPH | longitudinal study, follow-up study, panel study, incidence study |
| 相关≠ | 5 | 6 |
| 摘要≠ | The Cox proportional hazards model is a semi-parametric regression method that estimates the effect of one or more covariates on the hazard — the instantaneous rate of an event such as death, relapse, or failure — while making no assumption about the shape of the baseline hazard function. Introduced by David Cox in 1972, it is the dominant tool for multivariable survival analysis in clinical and epidemiological research. | A cohort study assembles a group of individuals who share a common starting point — typically freedom from the outcome of interest — and follows them over time to observe who develops the outcome. By comparing incidence rates between exposed and unexposed subgroups, researchers can estimate relative risk and absolute risk differences. Cohort studies are the gold-standard observational design for measuring disease incidence and establishing temporal relationships between exposure and outcome. |
| ScholarGate数据集 ↗ |
|
|